@article{042150b23286424ab78fe2559dd1c01f,
title = "Deep machine learning potentials for multicomponent metallic melts: Development, predictability and compositional transferability",
keywords = "ab initio simulations, Al-Cu-Ni alloys, Machine learning potential, Molecular dynamics, Multicomponent melts, Neural networks, DENSITY, ALUMINUM, ACCURATE, APPROXIMATION, LIQUID, COPPER",
author = "Ryltsev, {R. E.} and Chtchelkatchev, {N. M.}",
note = "Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",
year = "2022",
month = mar,
day = "1",
doi = "10.1016/j.molliq.2021.118181",
language = "English",
volume = "349",
journal = "Journal of Molecular Liquids",
issn = "0167-7322",
publisher = "Elsevier",
}